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ADDIE and SAM: instructional design models compared

Short answer

ADDIE is an instructional design model with five sequential phases: analysis, design, development, implementation and evaluation. SAM (Successive Approximation Model), by contrast, relies on short cycles with early prototypes and continuous feedback; ADDIE suits stable, well-plannable projects, SAM suits projects with unclear requirements or tight deadlines.

Key points

  • ADDIE: analysis, design, development, implementation, evaluation — thorough and plannable.
  • SAM: short cycles, early prototypes, continuous feedback — fast and adaptable.
  • Both models share the same core questions: who learns what, why, and does it work?
  • AI-assisted authoring shortens development and favours iterative work.
  • Evaluation belongs in every model, not just at the end.

Why use a design model?

Course development is a project with many participants: subject experts, authors, designers, technical staff, sponsors. Without a shared process, misunderstandings arise, changes come late and courses miss the need. Design models provide a structure in which everyone knows what to do when.

The two best-known models are ADDIE and SAM. They are not opposites but different answers to the question of how much you can plan in advance and how much you have to learn by trying.

ADDIE: five phases in sequence

ADDIE is an acronym of the model’s five phases. It comes from the systematic design of training and has been widespread for decades. In its classic form the phases run one after another, with the results of each phase preparing the next.

PhaseGuiding questionTypical outputs
AnalysisWhat need exists, who learns, under what conditions?Needs analysis, audience description
DesignWhich objectives, structure, methods and assessment?Learning objectives, outline concept, assessment plan
DevelopmentHow is the content produced?Slides, texts, media, exercises, exam
ImplementationHow does the course reach learners?Publication, assignment, support
EvaluationDid the course work?Analysis, improvements

Strengths and weaknesses of ADDIE

ADDIE’s strength is thoroughness. Anyone who analyses need and objectives carefully is less likely to build something nobody needs. The model suits projects with stable requirements, such as compliance training with a clear legal basis, and organisations that need traceability and documentation.

Its weakness is slowness. Design errors often only show up during implementation, when changes are expensive. Learners only see the course at the end. In many projects ADDIE is therefore applied iteratively today, with feedback loops and tests in every phase.

SAM: reaching the course in short cycles

SAM stands for Successive Approximation Model. Instead of planning everything first and then building, a simple prototype is created early, discussed with subject experts and learners and improved in short cycles. It starts with a brief preparation phase including a joint working session in which objectives, audience and first drafts are sketched out.

SAM’s strength lies in uncovering misunderstandings early. If learners see a rough draft after a week, you know immediately whether the approach works. The weakness: without discipline the cycle can run on forever, and documentation easily falls by the wayside. It has therefore proven useful to limit the number of cycles in advance, for example to three, and to fix for each cycle who gives feedback and by when.

  • Preparation: gather information, joint working session
  • Iterative design: draft, prototype, review, revision
  • Iterative development: build a version, test, improve until it works

Which model when?

ADDIE fits when requirements are clear and stable, many stakeholders need to be aligned and documentation matters. SAM fits when requirements are unclear, time is short or new formats are being tried. In practice many teams mix the two: analysis and objectives in the ADDIE style, development in SAM-style cycles.

AI-assisted tools shift the balance towards iterative work. When a first course draft can be produced from existing material in hours, a prototype is no longer an effort. You can show it to learners early, incorporate feedback and run several rounds before the course is published. The analysis at the start and the evaluation at the end lose none of their importance, though.

How Universe does it

The Universe workshop supports an iterative approach: material becomes a proposal with modules and slides, which you check and confirm; “View as student first” shows the course from the learner’s perspective, and a published course can be reverted to draft at any time. The slide editor keeps a history with named versions, so earlier states are preserved. For evaluation, knowledge levels and records are available.

Terms

ADDIE
A design model with the phases analysis, design, development, implementation and evaluation.
SAM
Successive Approximation Model: an iterative design model with early prototypes.
Evaluation
Assessing whether a course achieves its objectives and deriving improvements.
Prototype
An early, simplified version of a course used to test the approach before full development.
Iteration
One round of draft, test and improvement, repeated several times.

Frequently asked questions

What does ADDIE stand for?

Analysis, design, development, implementation and evaluation.

Is ADDIE outdated?

Not as a framework for thinking. Strictly linear application, however, is seen by many as too slow. Today ADDIE is often used iteratively, with feedback loops and tests in every phase.

What is a prototype in course development?

An early, simplified version of a course or module that subject experts and learners can use to check the approach before much effort goes into the full build.

Does a small team need a design model?

A lean one, yes. Even a short checklist covering analysis, objectives, draft, test and evaluation prevents the most common mistakes.

Where does AI fit into ADDIE or SAM?

AI mainly speeds up development: outline, narration, questions and graphics are created as drafts. Analysis, objectives, subject review and evaluation remain tasks for people. Because drafts are produced quickly, AI fits particularly well with iterative cycles.

How it works in Universe

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